Coding

pbl-loop

Try it

Use when the user asks for learning goals, capability development, reflection, teaching, replication, transfer readiness, or applying a PBL loop in a real project context. Operate in exactly three modes, start, checkpoint, transfer, to separate delivery evidence from capability evidence and track provenance.

What it does

Use when the user asks for learning goals, capability development, reflection, teaching, replication, transfer readiness, or applying a PBL loop in a real project context. Operate in exactly three modes, start, checkpoint, transfer, to separate delivery evidence from capability evidence and track provenance.

The skill document

PBL Loop (v0.1)

Use this skill for capability-learning loops in real work. It is host-neutral and dependency-free.

Trigger and boundary

Trigger only when the user explicitly requests:

  • a learning goal or capability-development objective,
  • reflection on what was learned versus what was delivered,
  • transfer, teaching, or replication against an adjacent problem,
  • a PBL-style growth loop in project context.

Do not trigger for:

  • routine project status updates,
  • delivery planning without learning/evidence intent,
  • generic study explanations,
  • final completion checks without a capability loop,
  • requests to change project truth or governance state directly.

Keep exactly three modes: start, checkpoint, transfer.

Start response contract (mandatory)

Treat start as a learning contract, not a full project plan.

If any key context is missing for:

  • delivery goal,
  • capability goal,
  • evidence context,

complete the mandatory schema with explicit unknown values, then ask exactly one focused question. Do not ask additional questions or add a full project plan. The response must end with that question.

When context is sufficient:

  • preserve the exact user delivery goal,
  • record one bounded user-facing capability goal,
  • keep all non-user-supplied details out of evidence fields,
  • never invent counts, durations, thresholds, percentages, score bands, windows, deadlines, or acceptance gates,
  • mark assistant additions as source_status: proposed and never convert them into hard requirements.

Core invariants (v0.1)

  • This skill is host-neutral. It does not require a specific host, CLI, MCP, fixed filesystem path, state backend, or external platform account.
  • It does not require host metadata or proprietary runtimes.
  • Preserve the real project delivery goal from user context. If unavailable, set delivery_goal to unknown and set status explicitly.
  • Use item-level source_status for each goal, requirement, proposal, unknown, and evidence item:
    • user_stated
    • unknown
    • proposed
  • Use item-level evidence_status for each evidence item:
    • observed
    • inferred
    • confirmed
    • unknown
  • Track assistance_provenance for every claim/step:
    • human
    • ai_reasoning
    • ai_tool
    • external_evidence
  • Distinguish evidence classes:
    • delivery evidence: shipped outputs, tests, artifacts, schedules, outcomes, acceptance signals.
    • capability evidence: repeatability, reasoning quality, transfer performance, teachability.
  • Default operation is conversation-only and stateless.
  • If the user authorizes persistence, store only user-approved notes in a user/host-selected project-local location.
  • Never overwrite prior project truth.

Four cognitive quadrants (state model)

Use these labels only for first-person capability/mastery claims, never for project status.

  1. known-known: user-confirmed capability with sufficient repeated, independent, or transfer evidence.
  2. known-unknown: named capability gap with defined test path but insufficient proof.
  3. unknown-known: repeated behavior indicates likely capability not yet recognized.
  4. unknown-unknown: anomaly or gap with no clear shape/test path yet.

Rules:

  • Move from unknown-known only when behavior suggests likely capability and is explicitly documented.
  • Move to known-unknown only when a gap is named and testable.
  • Move to known-known only after user-confirmed repeatable and transferable evidence.

Output schema (mandatory, all modes)

For every mode response, keep these top-level fields:

  • mode
  • delivery_goal
  • learning_goal
  • user_stated_requirements
  • assistant_proposals
  • unknowns
  • assistance_provenance
  • capability_debt
  • next_deliberate_challenge
  • quadrant_before and/or quadrant_after
  • delivery_evidence
  • capability_evidence

Each delivery_goal, learning_goal, user_stated_requirements, assistant_proposals, unknowns, delivery_evidence, and capability_evidence item must retain:

  • source_status
  • evidence_status
  • assistance_provenance

assistant_proposals should be empty when no proposal is needed; otherwise every proposal item must be clearly marked with source_status: proposed.

mode: start

Minimum required fields:

  • mode
  • delivery_goal
  • learning_goal
  • quadrant_before
  • user_stated_requirements
  • assistant_proposals
  • unknowns
  • assistance_provenance
  • capability_debt
  • next_deliberate_challenge
  • delivery_evidence
  • capability_evidence

Start logic:

  1. Restate the delivery goal with explicit status. If absent, set delivery_goal: unknown.
  2. Set one bounded first-person capability goal.
  3. Set baseline quadrant_before only for that capability claim.
  4. Add user facts to user_stated_requirements, missing context into unknowns.
  5. Put assistant additions in assistant_proposals with source_status: proposed.
  6. Keep delivery_evidence and capability_evidence as empty lists when no evidence is available; never omit the mandatory fields.
  7. If key context is still missing, end the response with exactly one focused question.

mode: checkpoint

  1. Carry forward the delivery goal and previous schema context.
  2. Add delivery/capability evidence updates and evidence status.
  3. Set quadrant_after to show capability movement.
  4. Keep capability_debt explicit.
  5. Set next_deliberate_challenge and any decision needed before continuation.

mode: transfer

  1. Carry forward the delivery goal from context; do not redefine it as the transfer task.
  2. Define one bounded adjacent problem in the same capability family.
  3. Enforce original-answer leakage control and avoid revealing prior exact wording/artifacts.
  4. Evaluate transfer for adaptability, explanation quality, and reuse.
  5. Update quadrant_before/quadrant_after and capability_debt.
  6. Use evidence_status for transfer judgments.

Anti-fabrication rule

  • Do not fabricate counts, durations, percentages, score bands, 24-hour windows, full intervention plans, or acceptance gates when missing.
  • Use unknown or proposed states instead of invented concrete values.

Fail-closed rule

Delivery polish and intervention quality do not prove capability. Capability claims still require evidence status and quadrant movement updates.

Optional companion note

FlowGrid (https://github.com/dlxeva/FlowGrid) is optional and only for durable cross-session judgment state when the user explicitly chooses it.

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